Zobrazeno 1 - 10
of 6 724
pro vyhledávání: '"Gokmen AN"'
Autor:
Rosenbaum, Andy, Kharazmi, Pegah, Banijamali, Ershad, Zeng, Lu, DiPersio, Christopher, Wei, Pan, Oz, Gokmen, Chung, Clement, Owczarzak, Karolina, Triefenbach, Fabian, Hamza, Wael
We present CALICO, a method to fine-tune Large Language Models (LLMs) to localize conversational agent training data from one language to another. For slots (named entities), CALICO supports three operations: verbatim copy, literal translation, and l
Externí odkaz:
http://arxiv.org/abs/2412.05388
3D head stylization transforms realistic facial features into artistic representations, enhancing user engagement across gaming and virtual reality applications. While 3D-aware generators have made significant advancements, many 3D stylization method
Externí odkaz:
http://arxiv.org/abs/2411.13536
Diffusion models have significant impact on wide range of generative tasks, especially on image inpainting and restoration. Although the improvements on aiming for decreasing number of function evaluations (NFE), the iterative results are still compu
Externí odkaz:
http://arxiv.org/abs/2411.12181
Coronary artery disease (CAD), one of the leading causes of mortality worldwide, necessitates effective risk assessment strategies, with coronary artery calcium (CAC) scoring via computed tomography (CT) being a key method for prevention. Traditional
Externí odkaz:
http://arxiv.org/abs/2411.07976
Aiming to accelerate the training of large deep neural models (DNN) in an energy-efficient way, an analog in-memory computing (AIMC) accelerator emerges as a solution with immense potential. In AIMC accelerators, trainable weights are kept in memory
Externí odkaz:
http://arxiv.org/abs/2410.15155
Autor:
Dai, Tianyuan, Wong, Josiah, Jiang, Yunfan, Wang, Chen, Gokmen, Cem, Zhang, Ruohan, Wu, Jiajun, Fei-Fei, Li
Training robot policies in the real world can be unsafe, costly, and difficult to scale. Simulation serves as an inexpensive and potentially limitless source of training data, but suffers from the semantics and physics disparity between simulated and
Externí odkaz:
http://arxiv.org/abs/2410.07408
Autor:
Li, Manling, Zhao, Shiyu, Wang, Qineng, Wang, Kangrui, Zhou, Yu, Srivastava, Sanjana, Gokmen, Cem, Lee, Tony, Li, Li Erran, Zhang, Ruohan, Liu, Weiyu, Liang, Percy, Fei-Fei, Li, Mao, Jiayuan, Wu, Jiajun
We aim to evaluate Large Language Models (LLMs) for embodied decision making. While a significant body of work has been leveraging LLMs for decision making in embodied environments, we still lack a systematic understanding of their performance becaus
Externí odkaz:
http://arxiv.org/abs/2410.07166
3D GAN inversion aims to project a single image into the latent space of a 3D Generative Adversarial Network (GAN), thereby achieving 3D geometry reconstruction. While there exist encoders that achieve good results in 3D GAN inversion, they are predo
Externí odkaz:
http://arxiv.org/abs/2409.20530
Recently, through development of several 3d vision systems, widely used in various applications, medical and biometric fields. Microsoft kinect sensor have been most of used camera among 3d vision systems. Microsoft kinect sensor can obtain depth ima
Externí odkaz:
http://arxiv.org/abs/2409.08847
Given the high economic and environmental costs of using large vision or language models, analog in-memory accelerators present a promising solution for energy-efficient AI. While inference on analog accelerators has been studied recently, the traini
Externí odkaz:
http://arxiv.org/abs/2406.12774